High-Entropy Perovskite Oxides as a Family of Electrocatalysts for Efficient and Selective Nitrogen Oxidation

催化作用 法拉第效率 氧化物 钙钛矿(结构) 氮气 氧气 材料科学 离解(化学) 析氧 动力学 无机化学 氧化还原 化学工程 化学 电化学 物理化学 电极 结晶学 有机化学 工程类 冶金 物理 量子力学 生物化学
作者
Hui Zheng,Yunxia Liu,Ziwei Ma,Elke Debroye,Jinyu Ye,Longsheng Zhang,Tianxi Liu
出处
期刊:ACS Nano [American Chemical Society]
卷期号:18 (27): 17642-17650 被引量:33
标识
DOI:10.1021/acsnano.4c02231
摘要

Electrocatalytic nitrogen oxidation reaction (NOR) can convert nitrogen (N2) into nitrate (NO3-) under ambient conditions, providing an attractive approach for synthesis of NO3-, alternative to the current approach involving the harsh Haber-Bosch and Ostwald oxidation processes that necessitate high temperature, high pressure, and substantial carbon emission. Developing efficient NOR catalysts is a prerequisite, which remains a formidable challenge, owing to the weak activation/dissociation of N2. A variety of NOR electrocatalysts have been developed, but their NOR kinetics are still extremely sluggish, resulting in inferior Faradaic Efficiencies. Here, we report a high-entropy Ru-based perovskite oxide (denoted as Ru-HEP) that can function as a high-performance NOR catalyst and exhibit a high NO3- yield rate of 39.0 μmol mg-1 h-1 with a Faradaic Efficiency of 32.8%. Both our experimental results and theoretical calculations suggest that the high-entropy configuration of Ru-HEP perovskite oxide can markedly enhance the oxygen-vacancy concentration, where the Ru sites and their neighboring oxygen vacancies can serve as unsaturated centers and decrease the overall energy barrier for N2 electrooxidation, thereby leading to promoted NOR kinetics. This work presents an alternative avenue for promoting NOR catalysis on perovskite oxides through the high-entropy engineering strategy.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
阿盛完成签到,获得积分10
刚刚
抒文发布了新的文献求助10
1秒前
Akim应助顺利的蓝血采纳,获得10
1秒前
科研通AI6应助萱棚采纳,获得30
1秒前
2秒前
Ki_Ayasato完成签到,获得积分10
2秒前
lmei发布了新的文献求助30
2秒前
3秒前
砡君应助拼搏的晓绿采纳,获得10
3秒前
3秒前
patato完成签到,获得积分10
3秒前
852应助耶耶采纳,获得10
3秒前
5秒前
热热发布了新的文献求助10
5秒前
希望天下0贩的0应助trans采纳,获得10
5秒前
6秒前
6秒前
hangzhen发布了新的文献求助10
6秒前
litpand发布了新的文献求助10
6秒前
Akim应助沉静老虎采纳,获得10
7秒前
镓氧锌钇铀应助李庭福采纳,获得10
7秒前
liputao完成签到 ,获得积分10
8秒前
JialiZhao完成签到,获得积分10
8秒前
8秒前
9秒前
大气葶应助Wan采纳,获得10
9秒前
踏实的道消完成签到 ,获得积分10
9秒前
NathanChen发布了新的文献求助10
10秒前
慕青应助简单雨柏采纳,获得10
10秒前
11秒前
11秒前
11秒前
蛋蛋发布了新的文献求助10
14秒前
Deanna完成签到 ,获得积分10
14秒前
15秒前
畅跑daily完成签到,获得积分10
15秒前
大气兔子完成签到,获得积分20
16秒前
hangzhen完成签到,获得积分10
16秒前
17秒前
18秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Treatise on Geochemistry (Third edition) 1600
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 1000
List of 1,091 Public Pension Profiles by Region 981
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Virus-like particles empower RNAi for effective control of a Coleopteran pest 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5458217
求助须知:如何正确求助?哪些是违规求助? 4564343
关于积分的说明 14294578
捐赠科研通 4489225
什么是DOI,文献DOI怎么找? 2458909
邀请新用户注册赠送积分活动 1448785
关于科研通互助平台的介绍 1424417